Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints

Zichao Wang, Andrew Lan, Richard Baraniuk


Abstract
We study the problem of generating arithmetic math word problems (MWPs) given a math equation that specifies the mathematical computation and a context that specifies the problem scenario. Existing approaches are prone to generating MWPs that are either mathematically invalid or have unsatisfactory language quality. They also either ignore the context or require manual specification of a problem template, which compromises the diversity of the generated MWPs. In this paper, we develop a novel MWP generation approach that leverages i) pre-trained language models and a context keyword selection model to improve the language quality of generated MWPs and ii) an equation consistency constraint for math equations to improve the mathematical validity of the generated MWPs. Extensive quantitative and qualitative experiments on three real-world MWP datasets demonstrate the superior performance of our approach compared to various baselines.
Anthology ID:
2021.emnlp-main.484
Volume:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2021
Address:
Online and Punta Cana, Dominican Republic
Editors:
Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
5986–5999
Language:
URL:
https://aclanthology.org/2021.emnlp-main.484
DOI:
10.18653/v1/2021.emnlp-main.484
Bibkey:
Cite (ACL):
Zichao Wang, Andrew Lan, and Richard Baraniuk. 2021. Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 5986–5999, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints (Wang et al., EMNLP 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/dois-2013-emnlp/2021.emnlp-main.484.pdf
Video:
 https://preview.aclanthology.org/dois-2013-emnlp/2021.emnlp-main.484.mp4
Data
MAWPSMath23KMathQA